Design and implementation of a Kiswahili mobile learning application incorporating machine learning through audio signal processing approach
Abstract
This project highlighted one of the most challenges underlying the low resource languages. As high
resource languages have vast amounts of data for training, Low resource languages have less data for
training. Quest for audio dataset for natural language (NL) processing tasks continue to draw research
interests globally. Thus a need to target low resource languages ;The basics and basis upon which
our project is determined with variable Audio analysis and processing which by farthest remains an
important aspect for information processing by computers.
To accomplish the project a visual and descriptive methodology was underlined: this consisted of
Research: through reading textbooks, journals, review articles, conference papers, tutorials And Other
relevant information from reliable sources, interviews with lecturers and professionals Hardware;
laptop and a mobile phone Software: Python programming language, Kotlin programming language,
Jetpack Compose, Google Colab, Matplotlib, Ipython, Numpy, Pandas, SkLearn, Keras and other
useful packages.
These were put together to have a fully functional mobile application. In this proposed work, a system
is developed and demonstrated. The model takes a sound wave as an input and gives a certain metric
of similarity as the output. The concepts of "Speech Recognition" and "Pattern Matching" are used
to create a Pronunciation Matching tool. This system can be used to enhance the pronunciation skills
of the Kiswahili language for people having Kiswahili as their second language. The tool matches
the similarity of utterance of a word by a speaker to the ideal pronunciation and gives a percentage
similarity or a metric to judge the pronunciation similarity.
The possible future works can be adding more data to create a data set with all words having two
classes, one for the correct pronunciation and another for the incorrect pronunciation.
This report therefore, consists of four chapters: Chapter one covers the introduction to our project,
definitions, problem statement, justification and objectives for the project. Chapter two covers the
literature review and all the theoretical knowledge about the project. Chapter three describes all
methodologies and practical work to be done in accomplishing the project. Chapter four outlines our
up to date progress about the project .